Postdoc/Research Assistant in Machine Learning for Health (f/m/x)

at  Helmholtz Zentrum Mnchen

102600
Full time
39 hrs./week
Neuherberg near Munich
Home Office Options
We are Helmholtz Munich. In a rapidly changing world, we discover breakthrough solutions for better health.
Our research is focused within the areas of metabolic health/diabetes, environmental health, molecular targets and therapies, cell programming and repair, bioengineering, and computational health. We particularly excel in the fields of basic research, bioengineering, artificial intelligence, and technological development.
Through this research, we build the foundations for medical innovation. Together with our partners, we seek to accelerate the transfer of our research, so that laboratory ideas can reach society and improve people’s quality of life at the fastest rate possible.
This is what drives us. Why not join us and make a difference?
The (AIH) at Helmholtz Munich is a European hub pioneering applied Artificial Intelligence (AI) and Machine Learning (ML) solutions for healthcare and clinical data analytics.
We are seeking postdoctoral researchers (f/m/x) in Machine Learning for Health to develop innovative AI methods addressing global health challenges, with a focus on translating these advancements into practical healthcare applications.
Prof. Matthias Tschöp (Dr. Med., Dr. hc.), CEO of Helmholtz Munich: “We believe that excellent research requires a range of different perspectives. Diverse teams reach better solutions and are more innovative in their research topics.
Establishing our Diversity Management Strategy demonstrates our commitment to ensuring an appreciative company culture based on mutual respect. We are also implementing diversity-sensitive processes throughout our whole organization.”
Your opportunity
In this role, you will create scalable AI solutions to analyze multimodal medical data, advancing patient stratification, disease progression prediction, and precision medicine for Tuberculosis.
Leveraging advanced models such as attention-based frameworks, transformers, and generative approaches, you will work with clinical trial data, electronic health records, and genomic biobanks.
Collaborative projects with leading global research consortia, industry, and international institutions will enable you to drive impactful research in global health.
Funded by Unite4Tb, a European initiative for innovative Tuberculosis treatments, this position offers a unique opportunity to apply your expertise and contribute to groundbreaking healthcare innovation on a global scale.

Your profile

• Ph.D. and/or postdoctoral experience with a strong background in machine learning, bioinformatics, computational biology, or a closely related field.
• Demonstrated expertise in developing and applying machine learning models (sklearn, etc) and deep learning frameworks (PyTorch, TensorFlow, etc.) for analysing biomedical data.
• Strong programming skills in Python are essential, with experience in processing large-scale datasets in a Linux/Bash environment.
• Experience with High Performance Computing (HPC) or cloud computing services (AWS, GCP).
• Proven track record of addressing clinical and biomedical research questions, with a strong focus on translational outcomes.
• Experience with large language models for analysing biomedical images and multi-omics data, and deep learning algorithms aimed at precision medicine.
• Knowledge in disease dynamics inference from clinical, epidemiological, and electronic health records data, and interest in fair AI practices for biomedical applications.
• A publication record in high-quality venues that demonstrates meaningful contributions to the field.
• Ability to work flexibly and collaboratively with a multidisciplinary team, including clinicians, epidemiologists, and representatives from health systems, particularly in developing settings within the area of Global Health.
• Excellent communication, organisation, leadership, and decision-making skills.

Benefits

• Career Development: Postdoc program, scientific training & career center with tailored offers
• Scientific Resources: State-of-the-art infrastruture and Core Facilities
• Recreation: 30 days annual leave, flexi days, plus public holidays
• International Staff Service: Support with the relocation and integration process in Germany
• Health Promotion: Sports, company doctor, mental health initiatives

Since 2005, we hold the TOTAL E-QUALITY award for exemplary action in the sense of an equal-opportunity organizational culture.
Helmholtz Munich is actively committed to diversity and inclusion in practice and is sustainably committed to equality.
The Diversity Charter has set itself the goal of promoting diversity in the world of work. By signing the charter, we commit ourselves to create an appreciative working environment for all employees.
If you fulfil all the requirements, you may be eligible for a salary grade of up to E 13. Social benefits are based on the Collective Wage Agreement for Public-Sector Employees (TVöD). The position has an (initial) fixed term of 3 years but may be extended under certain circumstances.
We are committed to promoting a culture of diversity and welcome applications from talented people regardless of gender, cultural background, nationality, ethnicity, sexual identity, physical abilities, religion or age. Qualified applicants with physical disabilities will be given preference.
If you have obtained a university degree abroad, we will require further documents from you regarding the comparability of your degree.
Interested in applying?
This is a joint position between Francesco Paolo Casale’s and Fabian Theis’ groups. If you have further questions, please reach out to francescopaolo.casale@helmholtz-muenchen.de.

Your application should include

• CV
• Cover letter
• Degrees/Diplomas/Certificates
• Contact details for at least two referees

We are Helmholtz Munich.
Why join us?
Helmholtz Munich
Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)
AI for Health
Ingolstädter Landstraße 1
85764 Oberschleißhei

Please refer the Job description for details